Age-related macular degeneration (AMD) is the leading cause of blindness in people 50 years or older in the developed world (Pascolini D et al, Ophthalmic Epidemiol 11, 67-115 (2004) and Jaeger R et al, N Engl J Med 358, 2602-2617 (2008); both of which are incorporated by reference herein). The advanced, neovascular form of AMD is characterized by the presence of choroidal neovascularization (CNV), pathologic new vessels from the choroid that grow into the avascular outer retina through breaks in Bruch's membrane (BM). CNV can lead to subretinal hemorrhage, fluid exudation, lipid deposition, detachment of the retinal pigment epithelium from the choroid, fibrotic scars, or a combination of these (Jaeger R et al, 2008 supra; De Jong P, N Engl J Med 355, 1474-1485 (2006); Donoso L et al, Surv Ophthalmol 51, 137-152 (2006); Stanga P et al, Ophthalmol 110, 15-21 (2003); incorporated by reference herein). Fluorescein (FA) and/or indocyanine green angiography (ICGA) have traditionally been used to detect and assess CNV in the clinic. However, these techniques are two-dimensional (2D) and involve intravenous dye injections, which can lead to nausea and anaphylaxis (Lopez-Saez M et al, Ann Allergy Asthma Immunol 81, 428-430 (1998); incorporated by reference herein).
Optical coherence tomography (OCT) is a noninvasive, depth resolved, volumetric imaging technique that is commonly used to visualize retinal morphology (Huang D et al, Science 254, 1178-1181 (1991); incorporated by reference herein). A limitation of conventional structural OCT is that it cannot be used to detect blood flow or discriminate vascular tissue from surroundings. To address this limitation, several OCT angiography methods have been proposed to identify blood flow at the microcirculation level (An L et al, Opt Express 16, 11438-11452 (2008); Yasuno Y et al, “Opt Express 15, 6121-6139 (2007); Grulkowsk I et al, Opt Express 17, 23736-23754 (2009); Fingler J et al, Opt Express 17, 22190-22200 (2009); Liu G et al, Opt Express 19, 3657-3666 (2011); incorporated by reference herein). Among these OCT angiography methods, the split-spectrum amplitude-decorrelation angiography (SSADA) algorithm is able to distinguish blood flow from static tissues based on detecting the reflectance amplitude decorrelation over consecutive cross-sectional B-scans at the same location (Jia Y et al, Opt Express 20, 4710-4725 (2012); Gao S et al, Opt Lett 40, 2305-2308 (2015); incorporated by reference herein). Moreover, segmentation of SSADA-based OCT angiograms can identify CNV as blood flow in the outer retina, a region devoid of blood flow in healthy eyes (Jia Y et al, Ophthalmology 121, 1435-1444 (2014); Jia Y et al Proc Natl Acad Sci USA 112, E2395-2402 (2015); de Carlo T et al, Ophthalmology 122, 1228-1238 (2015); Spaide R, Am J Ophthalmol 160, 6-16 (2015); Kuehlewein L et al, Eye (Lond) 29, 932-935 (2015); incorporated by reference herein). Despite these advances in OCT angiography delineation of CNV lesions from such datasets remains a challenge. The simplest method involves manual delineation by an experienced expert, but this approach is subjective, operator intensive, and time-consuming. Thus, a reliable and robust automatic detection method for quantifying the CNV lesion is needed in order to maximize the clinical utility of OCT angiography in the diagnosis of CNV and evaluation of the therapeutic effect of different treatments.